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Data Engineer

We believe small businesses are at the heart of our communities, and championing them is worth fighting for. We empower small business owners to manage their finances fearlessly, by offering the simplest, all-in-one financial management solution they can't live without.


Reporting to the Senior Manager of AI & Data Platform, as a Data Engineer you will be building tools and infrastructure to support efforts of the Data Products and Insights & Innovation teams, and the business as a whole.


We’re looking for a talented, curious self-starter who is driven to solve complex problems and can juggle multiple domains and stakeholders. This highly technical individual will collaborate with all levels of the Data and AI team as well as the various engineering teams to develop data solutions, scale our data infrastructure and advance Wave to the next stage in our transformation as a data-centric organization.


This role is for someone with proven experience in complicated product environments. Strong communication skills are a must to bridge the gap between technical and non-technical audiences across a spectrum of data maturity.


Here’s How You Make an Impact:
  • You’re a builder. You’ll be responsible for designing, building and deploying the components of a modern data stack, including CDC ingestion (using Debezium), a centralized Hudi data lake, and a variety of batch, incremental and stream-based pipelines.
  • You’ll make things better. You enjoy the challenge of helping build and manage a fault tolerant data platform that scales economically, while balancing innovation with operational stability by maintaining legacy Python ELT scripts and accelerating the transition to dbt models in Redshift.
  • You’re all about collaboration and relationships. You will collaborate within a cross-functional team in planning and rolling out data infrastructure and processing pipelines that serve workloads across analytics, machine learning and GenAI services. You enjoy working with different teams across Wave and helping them to succeed by ensuring that their data, analytics, and AI insights are reliably delivered.
  • You’re self-motivated and can work autonomously. We count on you to thrive in ambiguous conditions by independently identifying opportunities to optimize pipelines and improve data workflows under tight deadlines.
  • You will resolve and mitigate incidents: You will respond to PagerDuty alerts and proactively implement monitoring solutions to minimize future incidents, ensuring high availability and reliability of data systems.
  • You're a strong communicator. As a data practitioner, you’ll have people coming to you for technical assistance, and your outstanding ability to listen and communicate with people will reassure them as you help answer their concern.
  • You love helping customers. You will assess existing systems, optimize data accessibility, and provide innovative solutions to help internal teams surface actionable insights that enhance external customer satisfaction.


You Thrive Here By Possessing the Following:
  • Data Engineering Expertise: Bring 3+ years of experience in building data pipelines and managing a secure, modern data stack. This includes CDC streaming ingestion using tools like Debezium into a Hudi data lake that supports AI/ML workloads and a curated Redshift data warehouse.
  • AWS Cloud Proficiency: At least 3 years of experience working with AWS cloud infrastructure, including Kafka (MSK), Spark / AWS Glue, and infrastructure as code (IaC) using Terraform.
  • Strong Coding Skills: Write and review high-quality, maintainable code that enhances the reliability and scalability of our data platform. We use Python, SQL, and dbt extensively, and you should be comfortable leveraging third-party frameworks to accelerate development.
  • Data Lake Development: Prior experience building data lakes on S3 using Apache Hudi with Parquet, Avro, JSON, and CSV file formats.
  • Workflow Automation: Build and manage multi-stage workflows using serverless Lambdas and AWS Step Functions to automate and orchestrate data processing pipelines.
  • Data Governance Knowledge: Familiarity with data governance practices, including data quality, lineage, and privacy, as well as experience using cataloging tools to enhance discoverability and compliance.
  • CI/CD Best Practices: Experience developing and deploying data pipeline solutions using CI/CD best practices to ensure reliability and scalability.
  • Data Integration Tools: Working knowledge of tools such as Stitch and Segment CDP for integrating diverse data sources into a cohesive ecosystem.
  • Analytical and ML Tools Expertise: Knowledge and practical experience with Athena, Redshift, or Sagemaker Feature Store to support analytical and machine learning workflows is a definite bonus!


Succeeding at Wave:  At Wave, you’ll have the chance to grow and thrive by building scalable data infrastructure, enhancing a modern data stack, and contributing to high-impact projects that empower insights and innovation across the company. Whether collaborating in our vibrant downtown Toronto hub or working remotely, you’ll have the flexibility to shape your journey and make a lasting impact on Wave’s data-driven future. At Wave, we value diverse perspectives and encourage open, respectful feedback, fostering an inclusive environment where innovation flourishes, and every team member has the opportunity to grow.


At Wave, you’re treated like the incredible human being you are. 


Work From Where You Work Best: We will always have a welcoming, energizing, and world-class office (in Toronto) with a space for you. Or, if you’re more comfortable working from home, the choice is yours.

We Care About Future You: You will stretch yourself and you will grow at Wave. You will also be supported on this journey with diverse learning experiences, educational allowances, mentorship, and so much more.

We Support the Full You: We make a serious investment in your health & wellness. When we think about benefits we think about body, mind, & soul and we take this stuff very seriously. 

We Take Care of the Fundamentals: Fair compensation, all the office perks you’d want, and the various goodies you’d expect from a growing tech company. This is the obvious stuff, but we don’t want you to think we forgot!


We believe that a diverse and inclusive culture creates the best workplace. We embrace our differences, value individuality, and the broad spectrum of every Waver's skills and abilities. We challenge each other from a place of respect and pursuit of continuous growth. We trust each other and encourage everyone to bring their authentic selves to work, everyday. As Wavers, our voices matter, our opinions are met with an open mind. The best ideas win, no matter whose they are.  Contributing to an inclusive culture is a part of all of our job descriptions. 


We’ve been continuously recognized as one of Canada's Top Ten Most Admired Corporate Cultures and one of Canada’s Great Places to Work in categories including Technology, Millennials, Mental Health, Inclusion and Women.  


Are you ready to be a Waver? Join us!

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What You Should Know About Data Engineer, Wave HQ

As a Data Engineer at Wave in Toronto, Ontario, you'll play a pivotal role in empowering small business owners with reliable financial management solutions. Reporting to the Senior Manager of AI & Data Platform, you'll be instrumental in building tools and infrastructure that support our Data Products and Insights teams. We're looking for a talented and curious self-starter who loves tackling complex challenges and can efficiently juggle multiple domains and stakeholders. Your work will include designing and deploying a modern data stack, utilizing CDC ingestion with Debezium, and developing a centralized Hudi data lake. You'll also manage and improve our fault-tolerant data platform while maintaining legacy Python ELT scripts and transitioning to dbt models in Redshift. Collaboration is key; you’ll partner with various teams across Wave to ensure they have the data they need to succeed. Self-motivation and the ability to thrive in ambiguous conditions are essential as you identify opportunities to optimize data workflows. Your strong communication skills will be vital in bridging the gap between technical and non-technical colleagues. If you’re ready to innovate and help build a data-centric organization that values everyone's perspectives and contributions, Wave is the perfect place for you. Here, you’ll grow while making a significant impact in a company dedicated to supporting small businesses across Canada. Whether you choose to work from our vibrant Toronto office or from home, we provide the tools and encouragement you need to thrive both personally and professionally.

Frequently Asked Questions (FAQs) for Data Engineer Role at Wave HQ
What is the role of a Data Engineer at Wave?

At Wave, the Data Engineer is responsible for designing, building, and deploying components of a modern data stack. This includes managing data pipelines, developing data lakes, and collaborating with various teams to ensure the availability and reliability of data insights.

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What qualifications do I need to become a Data Engineer at Wave?

To qualify for the Data Engineer position at Wave, candidates should possess over 3 years of experience in building data pipelines, proficiency with AWS cloud infrastructure, and strong coding skills in Python and SQL. Experience with CDC ingestion, data lake development, and CI/CD best practices is also essential.

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What tools do Data Engineers at Wave use?

Data Engineers at Wave utilize various tools such as Debezium for CDC ingestion, Hudi for data lake creation, and AWS services like MSK, Glue, and Terraform for infrastructure management. Familiarity with dbt, Redshift, and data integration tools is also important.

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What environment will I be working in as a Data Engineer at Wave?

As a Data Engineer at Wave, you'll work in a collaborative and inclusive environment that values diverse perspectives. You can choose to work in our energetic downtown Toronto office or from your own home, allowing for flexibility in your work style.

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How does Wave support the professional growth of Data Engineers?

Wave is committed to the professional growth of its employees through various learning experiences, mentorship opportunities, and educational allowances. We emphasize continuous development and support your journey to thrive in your career.

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What is the company culture like at Wave?

Wave is recognized as one of Canada's Great Places to Work, emphasizing inclusivity, respect, and challenging each other towards continuous growth. We encourage all employees to bring their authentic selves to work and value every contribution.

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What impact can I make as a Data Engineer at Wave?

As a Data Engineer at Wave, you’ll have a significant impact on building scalable data infrastructure that empowers insights and innovation across the company, directly supporting small businesses and enhancing customer satisfaction.

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Common Interview Questions for Data Engineer
Can you describe your experience with CDC streaming ingestion and relevant tools?

In your response, share specific projects where you successfully implemented CDC ingestion, particularly using tools like Debezium. Discuss the challenges you faced and how you overcame them to facilitate the transition to a modern data stack.

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How do you ensure data quality and governance in your data engineering practices?

Discuss your experience with data governance practices, such as using data quality checks, lineage tracking, and privacy protocols. Provide examples of tools or strategies you've employed to maintain a reliable and compliant data environment.

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What strategies do you use to optimize data workflows?

Share techniques you’ve used to identify bottlenecks in data workflows and elaborate on how you’ve implemented changes to enhance efficiency. Mention examples of tools and methods that have led to measurable improvements in performance.

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How have you worked collaboratively with data scientists or analysts in the past?

Emphasize the importance of cross-functional collaboration and detail specific projects where you partnered with data scientists or analysts to deliver valuable data-driven insights, highlighting your communication skills and collaborative spirit.

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Describe a complex data problem you solved. What was your approach?

Provide a detailed account of a challenging data issue you faced, the steps you took to analyze and resolve it, and the impact of your solution on the overall data infrastructure and stakeholder satisfaction.

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Which programming languages and tools have you used in your data engineering work?

List the programming languages and tools you’re proficient in, such as Python, SQL, dbt, and AWS services. Discuss how you've applied these technologies in building and managing data pipelines and your approach to writing maintainable code.

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What are your experiences with cloud infrastructure, particularly AWS?

Discuss your hands-on experience working with AWS, including specific services you’ve utilized (e.g., S3, Redshift, Lambda) and how they contributed to building secure and scalable data solutions.

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How do you approach monitoring and incident response for data systems?

Explain your approach to monitoring data systems' health, including tools you’ve used to set up preventative measures. Share your protocol for responding to incidents and ensuring minimal downtime for stakeholders.

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What are the key components of a modern data stack, in your view?

Articulate your understanding of the essential components of a modern data stack, such as data lakes, data warehousing, ETL processes, and how they work together to support analytics and machine learning workflows.

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How do you keep up with the latest trends and technologies in data engineering?

Discuss your strategies for continuous learning within the data engineering field, whether through formal courses, attending industry conferences, or engaging with online communities. Share how you’ve applied new knowledge to your work.

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Founded in 2010 and headquartered in Toronto, Ontario, Wave Apps provides software solutions and related services for small business owners to manage finances.

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Full-time, hybrid
DATE POSTED
November 27, 2024

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